Climate-Smart Agriculture Platform using NASA-IBM Weather Model for Precision Farming
AgroClimate AI is an innovative platform that leverages NASA and IBM's weather prediction model to help farmers make informed decisions about their agricultural practices. By combining real-time climate data with advanced machine learning models, we provide actionable insights for sustainable and efficient farming.
agroclimate-ai/
βββ src/ # Source code
β βββ frontend/ # Frontend application (Next.js)
β βββ backend/ # Backend API services (FastAPI)
β βββ ml_model/ # Machine learning models
β βββ data_pipeline/ # Data processing pipelines
βββ docs/ # Documentation
βββ tests/ # Test suites
βββ scripts/ # Utility scripts
βββ config/ # Configuration files
- π°οΈ NASA-IBM Weather Model Integration
- π Real-time Climate Data Analysis
- π€ Machine Learning-based Predictions
- π± Crop Recommendation System
- β‘ Real-time Alerts and Notifications
- π± Farmer-friendly Dashboard
- π Historical Data Analysis
- π― Precision Agriculture Support
- Python 3.8+
- Node.js 16+
- Docker (optional)
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Clone the repository:
git clone https://github.com/Roxonn-FutureTech/agroclimate-ai.git cd agroclimate-ai -
Install dependencies:
# Backend dependencies cd src/backend pip install -r requirements.txt # Frontend dependencies cd ../frontend npm install
-
Set up environment variables:
cp config/.env.example config/.env
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Start the development servers:
# Backend cd src/backend uvicorn main:app --reload # Frontend cd ../frontend npm run dev
We welcome contributions! Please see our Contributing Guide for details.
This project is licensed under the MIT License - see the LICENSE file for details.
- Website: roxonn.com
- GitHub: @Roxonn-FutureTech